PyClone is statistical model and software tool designed to infer the prevalence of point mutations in heterogeneous cancer samples. The input data for PyClone consists of a set read counts from a deep sequencing experiment, the copy number of the genomic region containing the mutation and an estimate of tumour content.

References:

• Roth et al. PyClone: statistical inference of clonal population structure in cancer PMID: 24633410

• https://github.com/aroth85/pyclone

• Module Name: pyclone (see the modules page for more information)
• Example files in /usr/local/apps/pyclone/examples

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive --mem=10g
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144 ~]$ module load pyclone
[user@cn3144 ~]$ cp -r /usr/local/apps/pyclone/examples /data/$USER
[user@cn3144 ~]$ cd /data/$USER/examples/mixing/tsv
[user@cn3144 ~]$ PyClone run_analysis_pipeline --in_files SRR385939.tsv SRR385940.tsv SRR385941.tsv --working_dir pyclone_analysis
[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$

This will create a directory pyclone_analysis. After the command completes the directory will contain several folders and the file config.yaml:

• config.yaml
• plots/
• tables/
• trace/
• yaml/

• config.yaml - This file specifies the configuration used for the PyClone analysis.
• plots - Contains all plots from the analysis. There will be two sub-folders clusters/ and loci/ for cluster and locus specific plots respectively.
• tables - This contains the output tables with summarized results for the analysis. There will be two tables clusters.tsv and loci.tsv, for cluster and locus specific information.
• trace - This the raw trace from the MCMC sampling algorithm. Advanced users may wish to work with these files directly for generating plots and summary statistics.

Create a batch input file (e.g. batch.sh). For example:

#!/bin/bash
set -e
module load pyclone
PyClone run_analysis_pipeline --in_files SRR385939.tsv SRR385940.tsv SRR385941.tsv --working_dir pyclone_analysis

Submit this job using the Slurm sbatch command.

sbatch [--mem=#] batch.sh

Create a swarmfile (e.g. job.swarm). For example:

cd dir1;PyClone ...
cd dir2;PyClone ...
cd dir3;PyClone ...
cd dir4;PyClone ...

Submit this job using the swarm command.

swarm -f job.swarm [-g #] --module pyclone